Google: “We’re excited to integrate content testing into Google Analytics and believe it will help meet your goals of measuring, testing and optimizing all in one place. Content Experiments helps you optimize for goals you have already defined in your Google Analytics account, and can help you decide which page designs, layouts and content are most effective. With Content Experiments, you can develop several versions of a page and show different versions to different visitors. Google Analytics measures the efficacy of each page version, and with a new advanced statistical engine, it determines the most effective version. … Testing and experimentation of websites may sound complicated, but we’ve worked hard to provide a testing tool that makes it as easy as possible: Content Experiments comes with a setup wizard that walks you step by step through setting up experiments, and helps you quickly launch new tests. Content Experiments reuses Google Analytics tags so that you only need to add one additional tag to the original page. Content Experiments helps you understand which content performs best, and identifies a winner as soon as statistically significant data has been collected. Since content testing is so important, we’ve placed Content Experiments just a click away from your regular diagnosis reports in Google Analytics. – With full integration in Google Analytics, we’ll be able to grow and evolve website experimentation tools within our broader measurement platform. Initially, you’ll be able to utilize important features like optimized goal conversions, easier tagging, and advanced segmentation in reports. We’re also working hard to release page metrics, additional goal conversion options and experiment suggestions.”

LM: “Google Website Optimizer is Dead. Long live Google Analytics Content Experiments… This is the all new, tied directly into your analytics, testing software to replace Google Website Optimizer. Google Website Optimizer will slowly be decomissioned over this year, and replaced fully by these new Content Experiments. So if your’e starting any A/B testing anytime soon, time to do it in here rather than in GWO. … On the whole I’m pretty excited to have Content Experiments tied into Google Analytics. There are a number of benefits to the new system. There’s only one code snippet you need to include on the page rather than multiple pages of code. It really simplifies that aspect when you need to add new testing. You can also now use advanced segments to segment your results too. There’s some improved statistical models too. Test results don’t even show up for 2 weeks or more, and all tests expire after 3 months, assuming you can’t get a statistically significant winner. If you have a lot of traffic that’ll undoubtedly be true, but it’ll make it harder to do longer tests on lower traffic sites. All in all though I think it’s great. If I had one wish it’d be to add Multivariate testing as well as just A/B testing. You can do MVT and pretend through an A/B test but it’s much more awkward.”

OB: “Google Analytics Content Experiments – A Guide To Creating A/B Tests – In this post I go over the new Google Analytics Content Experiments, a tool that can be used to create A/B tests from inside Google Analytics. This tool has several advantages over the old Google Website Optimizer, especially if you are just starting the website testing journey. Content Experiments provide a quick way to test your main pages (landing pages, homepages, category pages) and it requires very few code implementations. … All in all, Google Analytics has made a great job out of this new testing capability, especially for marketers that are still not testing often. For marketers that are more advanced there are still quite a few features missing.”

Google: “We integrated content testing into Google Analytics to help you meet your goals of measuring, testing, and optimizing all in one place. Content Experiments helps you optimize for goals you have already defined in your Google Analytics account, and can help you decide which page designs, layouts, and content are most effective. With Content Experiments, you can develop several versions of a page and show different versions to different visitors. Google Analytics measures the efficacy of each page version, and with a new advanced statistical engine, it determines the most effective version.”

Google: “Content Experiments is a somewhat different approach from either standard A/B or multivariate testing. Content Experiments is more A/B/N. You’re not testing just two versions of a page as in A/B testing, and you’re not testing various combinations of components on a single page as in multivariate testing. Instead, you are testing up to five full versions of a single page, each delivered to visitors from a separate URL.”

Google: “Before you use Content Experiments, you need to create a Google account if you don’t have one, create a Google Analytics account, and add the Analytics tracking code to your web pages.”

Google: “Content Experiments has three main areas: the experiment-setup wizard, the list of experiments, and the individual reports for each experiment. In addition, you can also see data about your experiment in your Google Analytics profile.”

Google: “Analytics Goals You can Use in Experiments – You set up goals in Google Analytics, and then use those goals as the basis for your experiments. URL Destination goals: An experiment that uses a URL Destination goal focuses on getting visitors to view a specific web page. Use this kind of goal to find out things like how well your test pages encourages visitors along a path to a product page, a page that includes the location of your business, or pages on which you’re selling ads. – Event goals: An experiment that uses an event goal focuses on getting visitors to perform a specific action on a page. Use this kind of goal to find out things like how well your test pages encourages visitors to sign up for a newsletter, view a video, or click Add to Cart for a product. – Visit Duration goals: Use this kind of goal to see how well your test pages encourage visitors to spend at least the minimum amount of time you want on your site. For example, if you’re running a news site, you want to see that visitors are spending enough time to read the articles, and enough time to validate the rates you charge for advertisements. – Pages per Visit goals: Like visit-duration goals, pages-per-visit goals help you understand whether visitors are consuming the amount of content you want. Are they browsing enough product pages; are they reading articles in the political, sports, and lifestyle sections?”

Google: “Multi-armed bandit experiments – The name comes from a stylized experiment involving several slot machines (‘one-armed bandits’) with potentially different expected payouts. You want to find the strategy that maximizes expected revenue. There are highly-developed mathematical models for solving this problem, which we have used to develop techniques for Content Experiments. … Experiments based on multi-armed bandits can be much cheaper than ‘classical’ A-B experiments. They’re also just as statistically valid, and in some circumstances they can produce answers more quickly. They’re cheaper because they move traffic towards winning variations gradually, instead of forcing you to wait for a ‘final answer’ at the end of an experiment. They can be faster because samples that would have gone to obviously inferior variations can be assigned to potential winners. The extra data collected on the high performing variations can help separate the ‘good’ ones from the ‘best’ ones more quickly.”

Google: “Cloaking is the practice of presenting a version of a web page to search engines that is different from the version presented to visitors, with the intention of deceiving the search engines and affecting the page’s ranking in the search index. – Google does not view the ethical use of testing tools such as Content Experiments to constitute cloaking.”

Google: “To ensure that serving your variation pages does not have a negative impact on your site’s SEO rankings, you can use the rel=”canonical” link attribute on your variation pages. rel=”canonical” is a signal to search engines that the content of your variation pages is essentially the same as that of your original page, and that you would prefer that search engines index your original page rather than the variations you’re using in your experiment.”